CivArchive
    orangeHong/allin-face-3-moss-sft - c1-st6000
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    # 偶映-虚拟脸模3-moss-sft ## 模型介绍 本模型依托魔搭社区(ModelScope)AIGC专区[模型训练](https://modelscope.cn/aigc/modelTraining)环境与算力完成训练。 * 模型类型:LoRA * 基础模型:[openmoss/MOSS-Image-SFT](https://modelscope.cn/models/openmoss/MOSS-Image-SFT) * 训练代码:[DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) * 训练数据量:10 * 总训练步数:6000 * 开源协议:Apache-2.0 ## 推理代码 安装 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio): ```bash pip install diffsynth ``` 开始推理: ```python from diffsynth.pipelines.moss_image import MOSSImagePipeline, ModelConfig import torch pipe = MOSSImagePipeline.from_pretrained( torch_dtype=torch.bfloat16, device="cuda", model_configs=[ ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"), ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="text_encoder/model*.safetensors"), ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="vae/diffusion_pytorch_model.safetensors", computation_dtype=torch.float32), ], tokenizer_config=ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="tokenizer/"), ) pipe.load_lora(pipe.dit, ModelConfig(model_id="orangeHong/allin-face-3-moss-sft", origin_file_pattern="allin-face-3-moss-sft_c1-st6000.safetensors")) prompt = "a cat" image = pipe(prompt, height=1024, width=1024, seed=0, num_inference_steps=50, cfg_scale=3.0) image.save("image.jpg") ```

    Description

    LoRA
    MOSS-Image-SFT

    Details

    Downloads
    12
    Platform
    Civision
    Platform Status
    Available
    Created
    10/26/2026
    Updated
    10/26/2026
    Deleted
    -

    Files

    allin-face-3-moss-sft_c1-st6000.safetensors